The Next Chapter in AI for Marketing
At a glance
- Causal AI gives marketers data-driven insight into what truly drives their customers, and recommends initiatives that are best placed to influence customer behaviours.
- Causal AI adopters are supercharging marketing effectiveness, revolutionizing the way data informs decision-making and transforming the customer journey.
The challenge with legacy AI/ML
Legacy Machine learning (ML) is designed to make predictions. It finds correlations and projects them into the future. However, the essence of marketing is not making predictions — it is understanding and influencing the customer.
To compound the problem, ML generates untrustworthy results. ML models are black boxes that marketers can’t verify or scrutinize. They tend to overfit to the current market conditions. And to function at all they need very big data — emerging trends, rare purchases, and unusual customer behaviors can lead to tech meltdowns.
Towards a causal marketing world
Causal AI is the only type of AI capable of addressing the core questions marketers care about.
Causes not correlations
Causal models give marketers superpowers! They capture the factors that really drive customer behaviors, and disregard irrelevant information — and they are inherently explainable.
Causal AI identifies the most persuadable customers to focus marketing budget on.
Causal models make it possible to hyper-personalize treatments to individual customers at scale: the holy grail of marketing.
Causal models also allow for a higher-level view. Marketers can feed the AI business objectives, goals, and constraints, which it uses to optimize decisions for individual customers.
End-to-end service across the customer journey
Causal models reveal a complete picture of what drives the customer journey. Marketers can link their models to build better experiences and outcomes across the journey.
The new marketing AI playbook
causaLens has developed a stack of solutions for marketing, running on the world’s most advanced Causal AI technology. Interested in finding out more? Request a demo